Data Warehouse Technology Migration to Databricks

A communications company with a legacy columnar MPP technology cluster containing hundreds of terabytes of data in its on-premises infrastructure was facing performance, data flexibility, and cost challenges. Therefore, it decided to migrate its analytics repository to Databricks.

Challenges

The company was facing several challenges because its ingestion processes were not standardized and because there was insufficient governance of processes and workflows within its data warehouse-type analytical repository.

Volumen alto de datos.

Falta de documentación y gobierno de procesos actuales.

Falta de procesos de validación de información.

Retos de vencimiento y desactualización tanto de la infraestructura de hardware como de las licencias de software.

Therefore, the project had to be executed in the short term.

Implemented Solution

Migration of MPP technology deployed in on-premises infrastructure to the Azure cloud with Databricks

During the migration, it was necessary to understand these structures and migrate them to a more optimal environment, a cloud deployment. So, we carried out a migration of MPP technology from a cluster of dozens of nodes to Databricks on Azure. This included all ingestion processes, translation, and implementation of SQL business rules to SQL technology in DBx. Process optimization was carried out based on the infrastructure to be used (cluster type and machine type) to improve performance and reduce costs, while also standardizing processes to simplify operations.

Achievements

Translation and updating of business rules programming.
Establishment of governance processes in a reusable and standardized framework.
Performance improvement metrics.
Cost improvements.
Process standardization to simplify operations.
With this migration, the company was able to upgrade to state-of-the-art technology, operate in a cloud environment, modernize processes, and streamline spending.